[Hiring] Data and Machine Learning Intern @Loka, Inc

Role Description

As a Data - Machine Learning Intern, you'll gain professional experience supporting Loka’s certified specialists, technical experts and PhDs while elevating your skillset, building a portfolio and launching projects you’re proud of.

• Assist in designing, developing and maintaining data pipelines to ensure clean, reliable and timely data.
• Collaborate with the team to implement and optimize ETL processes.
• Integrate data from various sources into warehouses, data lakes and lakehouses.
• Support data management tasks, including data cleaning, validation and transformation.
• Understand business objectives and develop models that help achieve them, plus metrics to track their progress.
• Implement ML systems using classical ML, DL and Foundation Models following best practices.
• Participate in client communications by helping gather requirements and communicate deliverables.
• Explore and visualize data with a careful eye for issues that require data cleaning as well as differences in data distribution that may affect performance after deployment.
• Identify and analyze model errors.

Qualifications

• Last year of a bachelor’s degree in Computer Science or related.
• Proficient in English.
• Basic knowledge of Python, ML, and Data libraries.
• Basic knowledge of Databases.
• Understanding of statistical, ML and deep learning algorithms.
• Experience visualizing and manipulating big datasets.
• Problem solving.
• Bonus: AWS knowledge, (Py)Spark, Airflow, Data Lakes and Data Warehouses.

Requirements

• Curiosity: You’re ambitious to learn and grow in different industries utilizing a modern tech stack.
• Autonomy and positivity: We’re a fully remote, globally distributed team.
• Teamwork: Enjoy a collaborative approach.
• Adaptability: Operate with a startup mindset and move at a startup pace.
• Dependable: You can be trusted to deliver high-quality work.

Benefits

• Every other Friday off.
• Health Bonus.
• Remote and flexible.
• Paid sick days and local holidays.